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Field
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system automation. Investigate and improve human-machine interaction frameworks for construction operations, including robotics, sensor-based communication, and real-time monitoring. Publish research
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-matter interactions, development of automated AI/ML systems for novel materials processing and quality insurance. The lab combines additive manufacturing, large scale laser micro-processing, multiscale
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design, prototyping, testing, and refinement of robotic systems and automation solutions, including sensor integration and feedback control. Collaborate with a multidisciplinary team to design and execute
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algorithmic perspectives on large language models Statistical learning theory and complexity analysis Automated theorem proving and formal methods Random matrix theory and its applications in modern AI systems
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calculations, data analysis, and experiment design. -On the mathematical side, the group designs neuro-symbolic techniques to automate theoretical physics calculations, integrating AI agents with physics
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described in a Scottish Government High Growth Spinout award focused on the commercialisation of research work relating to the development of an automated water monitoring system for waterborne pathogens, and
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taxonomy in AI-assisted workflows Prototype and test automated classification scripts (Python/R) Document data pipelines and QA/QC procedures Supervision & Training Mentor PhD-level and undergraduate RAs
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language models Statistical learning theory and complexity analysis Automated theorem proving and formal methods Random matrix theory and its applications in modern AI systems This position can be filled
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(e.g., finite element or wave propagation simulations) for defect detection and materials analysis Integrate AI, machine learning, and robotics into NDE and manufacturing processes for automation and
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automation—specifically motion planning, path optimization, sensor fusion, or robot learning—ideally with ROS or embedded systems experience; proficient in written and spoken English; good communication